Papers by Ahmad Aghaebrahimian
Towards Integration of Statistical Hypothesis Tests into Deep Neural Networks (P19-1)
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| Challenge: | Existing approaches for text classification are lexicallevel features with Naive Bayes or Support Vector Machines (SVM) . |
| Approach: | They propose a deep-learning model that uses label descriptions to train texts and their labels for multi-label and multi-class classification tasks. |
| Outcome: | The proposed model improves on one set with a high margin and on all other sets with competitive results. |
Deep Neural Networks at the Service of Multilingual Parallel Sentence Extraction (C18-1)
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| Challenge: | Existing models for parallel data harvesting from Wikipedia are language-independent, robust and highly scalable. |
| Approach: | They propose an end-to-end neural model for large-scale parallel data harvesting from Wikipedia . their model is language-independent, robust, and highly scalable . |
| Outcome: | The proposed model is language-independent, robust, and highly scalable. |